Ronnie Zipkin1, Andrew Schaefer2, Mary Chamberlin3,4,5,6, Tracy Onega2,7,8,9, Alistair J O'Malley1,2,5, Erika L Moen1,2,5. 1. Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 2. The Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, NH, USA. 3. Department of Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 4. Department of Hematology-Oncology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA. 5. Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA. 6. Comprehensive Breast Program, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 7. Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA. 8. Department of Population Sciences, University of Utah, Salt Lake City, UT, USA. 9. Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Abstract
BACKGROUND: Drivers behind the adoption of gene expression profiling in breast cancer oncology have been shown to include exposure to physician colleagues' use of a given genomic test. We examined adoption of the Oncotype DX 21-gene breast cancer recurrence score assay (ODX) in the United States after its incorporation into clinical guidelines. The influence of patient-sharing ties and co-location with prior adopters and the role of these potential exposures across medical specialties on peers' adoption of the test were examined. METHODS: We conducted a retrospective cohort study of women with incident breast cancer using a 100% sample of fee-for-service Medicare enrollee claims over 2008-2011. Peer networks connecting medical oncologists and surgeons treating these patients were constructed using patient-sharing and geographic co-location. The impact of peer connections on the adoption of ODX by physicians and testing of patients was modeled with multivariable hierarchical regression. RESULTS: Altogether, 156,229 women identified with incident breast cancer met criteria for cohort inclusion. A total of 7689 ODX prescribing physicians were identified. Co-location with medical oncologists who adopted the test in the early period (2008-2009) was associated with a 1.38-fold increase in the odds of a medical oncologist adopting ODX in 2010-2011 (95% CI = 1.04-1.83), as was co-location with early-adopting surgeons (odds ratio [OR] = 1.25, 95% CI = 1.00-1.58). Patients whose primary medical oncologist was linked to an early-adopting surgeon through co-location (OR = 1.17, 95% CI = 1.04-1.32) or both patient-sharing and co-location (OR = 1.17, 95% CI = 1.03-1.34) were more likely to receive ODX. CONCLUSIONS: Exposure to surgeon early adopters through peer networks and co-location was predictive of ODX uptake by medical oncologists and testing of patients. Interventions focused on the role of surgeons in molecular testing may improve the implementation of best practices in breast cancer care.
BACKGROUND: Drivers behind the adoption of gene expression profiling in breast cancer oncology have been shown to include exposure to physician colleagues' use of a given genomic test. We examined adoption of the Oncotype DX 21-gene breast cancer recurrence score assay (ODX) in the United States after its incorporation into clinical guidelines. The influence of patient-sharing ties and co-location with prior adopters and the role of these potential exposures across medical specialties on peers' adoption of the test were examined. METHODS: We conducted a retrospective cohort study of women with incident breast cancer using a 100% sample of fee-for-service Medicare enrollee claims over 2008-2011. Peer networks connecting medical oncologists and surgeons treating these patients were constructed using patient-sharing and geographic co-location. The impact of peer connections on the adoption of ODX by physicians and testing of patients was modeled with multivariable hierarchical regression. RESULTS: Altogether, 156,229 women identified with incident breast cancer met criteria for cohort inclusion. A total of 7689 ODX prescribing physicians were identified. Co-location with medical oncologists who adopted the test in the early period (2008-2009) was associated with a 1.38-fold increase in the odds of a medical oncologist adopting ODX in 2010-2011 (95% CI = 1.04-1.83), as was co-location with early-adopting surgeons (odds ratio [OR] = 1.25, 95% CI = 1.00-1.58). Patients whose primary medical oncologist was linked to an early-adopting surgeon through co-location (OR = 1.17, 95% CI = 1.04-1.32) or both patient-sharing and co-location (OR = 1.17, 95% CI = 1.03-1.34) were more likely to receive ODX. CONCLUSIONS: Exposure to surgeon early adopters through peer networks and co-location was predictive of ODX uptake by medical oncologists and testing of patients. Interventions focused on the role of surgeons in molecular testing may improve the implementation of best practices in breast cancer care.
Authors: E J Stanek; C L Sanders; K A Johansen Taber; M Khalid; A Patel; R R Verbrugge; B C Agatep; R E Aubert; R S Epstein; F W Frueh Journal: Clin Pharmacol Ther Date: 2012-01-25 Impact factor: 6.875
Authors: Niam Yaraghi; Anna Ye Du; Raj Sharman; Ram D Gopal; R Ramesh; Ranjit Singh; Gurdev Singh Journal: J Am Med Inform Assoc Date: 2013-11-28 Impact factor: 4.497
Authors: Yonina R Murciano-Goroff; Anne Marie McCarthy; Mirar N Bristol; Peter Groeneveld; Susan M Domchek; U Nkiru Motanya; Katrina Armstrong Journal: Breast Cancer Res Treat Date: 2018-05-08 Impact factor: 4.872
Authors: Michaela A Dinan; Xiaojuan Mi; Shelby D Reed; Bradford R Hirsch; Gary H Lyman; Lesley H Curtis Journal: JAMA Oncol Date: 2015-05 Impact factor: 31.777
Authors: Tina W F Yen; Liliana E Pezzin; Jianing Li; Rodney Sparapani; Purushuttom W Laud; Ann B Nattinger Journal: Cancer Date: 2016-11-08 Impact factor: 6.860
Authors: Kelly D Blake; Jennifer L Moss; Anna Gaysynsky; Shobha Srinivasan; Robert T Croyle Journal: Cancer Epidemiol Biomarkers Prev Date: 2017-06-09 Impact factor: 4.254
Authors: Craig Evan Pollack; Gary E Weissman; Klaus W Lemke; Peter S Hussey; Jonathan P Weiner Journal: J Gen Intern Med Date: 2012-06-14 Impact factor: 5.128
Authors: Mackenzie R Bronson; Nirav S Kapadia; Andrea M Austin; Qianfei Wang; Diane Feskanich; Julie P W Bynum; Francine Grodstein; Anna N A Tosteson Journal: Med Care Date: 2018-12 Impact factor: 2.983
Authors: Matthew D Nemesure; Thomas M Schwedhelm; Sofia Sacerdote; A James O'Malley; Luke R Rozema; Erika L Moen Journal: Appl Netw Sci Date: 2021-07-17